class_docstr: The Missing Values Dispersion visualizer shows the locations of missing (nan)
  values in the feature dataset by the order of the index.
  
  When y targets are supplied to fit, the output dispersion plot is color
  coded according to the target y that the element refers to.
  
  Parameters
  ----------
  alpha : float, default: 0.5
      A value for bending elments with the background.
  
  marker : matplotlib marker, default: |
      The marker used for each element coordinate in the plot
  
  classes : list, default: None
      A list of class names for the legend.
      If classes is None and a y value is passed to fit then the classes
      are selected from the target vector.
  
  kwargs : dict
      Keyword arguments that are passed to the base class and may influence
      the visualization as defined in other Visualizers.
  
  Attributes
  ----------
  features_ : np.array
      The feature labels ranked according to their importance
  
  classes_ : np.array
      The class labels for each of the target values
  
  Examples
  --------
  
  >>> from yellowbrick.contrib.missing import MissingValuesDispersion
  >>> visualizer = MissingValuesDispersion()
  >>> visualizer.fit(X, y=y)
  >>> visualizer.show()
docstr: Draws a multi dimensional dispersion chart, each color corresponds
  to a different target variable.
docstr_tok: ["Draws","a","multi","dimensional","dispersion","chart",",","each","color","corresponds","to","a","different","target","variable","."]
code: def draw_multi_dispersion_chart(self, nan_locs):
      """Draws a multi dimensional dispersion chart, each color corresponds
      to a different target variable.
      """
      for index, nan_values in enumerate(nan_locs):
          label, nan_locations = nan_values
  
          # if features passed in then, label as such
          if self.classes_ is not None:
              label = self.classes_[index]
  
          color = self.colors[index]
  
          x_, y_ = list(zip(*nan_locations))
          self.ax.scatter(
              x_,
              y_,
              alpha=self.alpha,
              marker=self.marker,
              color=color,
              label=label,
          )
  
file_path: yellowbrick/yellowbrick/contrib/missing/dispersion.py
imports: import numpy
  from yellowbrick.style.palettes import color_palette
  from .base import MissingDataVisualizer
label_desc: Use image node_id 4 for calling the MissingValuesDispersion obj's underlying member method code with example usage: obj.draw_multi_dispersion_chart(nan_locs) without return types